Search Results (12,643)

Acoustic emission (AE) sensing is widely used for structural health monitoring, but conventional piezoelectric sensors can be constrained in high-temperature and radiation environments. This study evaluates whether an Idaho National Laboratory-developed magnetostrictive AE sensor retains sufficient information for automated impact-source classification under a controlled room-temperature configuration. A total of 334 synchronized acquisitions from six impact classes were recorded at 20 MHz using three fixed, non-coincident sensor channels. Because sensor type was not independently varied from position, mounting, coupling, bandwidth, or propagation path, comparisons represent complete sensor-channel responses rather than isolated transduction mechanisms. Each waveform was represented by 16 time-domain, spectral, and band-power features. Random forest classifiers were evaluated for individual channels, 48-feature fusion, and equal-vote decision fusion using 30 repeated stratified holdout runs and stratified 10-fold cross-validation. The magnetostrictive channel achieved 95.35 ± 2.45% mean holdout accuracy, compared with 92.37 ± 2.94% and 96.31 ± 1.98% for the two commercial channels. Feature-level fusion achieved 97.12 ± 2.19% and 97.91 ± 3.18% under holdout and 10-fold cross-validation, respectively. Because class-specific blocks were split at the event level, these accuracies are within-campaign and within-specimen, may be optimistic, and do not establish block-independent or operational generalization; validation using randomized or interleaved repeated blocks, multiple specimens, position-controlled comparisons with swapped, rotated, or co-located sensor placements, and harsh-environment testing remains necessary. Full article

Background: Immersive virtual reality (VR) may support rehabilitation and patient engagement; however, little is known about how frontline healthcare professionals perceive its clinical relevance and feasibility in post-acute community care settings. This study explored healthcare professionals’ perceptions of the potential clinical uses, usability, and implementation requirements of patient-facing immersive VR in a community hospital providing post-acute care in Singapore. Methods: Using purposive sampling, nineteen healthcare professionals from a subacute hospital in Singapore participated in individual semi-structured interviews. Participants discussed their expectations of VR, experienced approximately 10–15 min of a reminiscence-oriented virtual tour of a local (now defunct) village, using an Oculus Quest head-mounted display, and subsequently reflected on its usability and potential applications. The Unified Theory of Acceptance and Use of Technology 2 informed the interview guide and was used as a sensitising framework. Interviews were transcribed verbatim and analysed using hybrid deductive–inductive framework analysis. Results: Four themes were identified: (1) clinical value was conditional on therapeutic relevance; (2) anticipated patient acceptability depended on person–content fit and social context; (3) simple navigation did not remove physical and sensory barriers; and (4) clinical integration required a supporting service model. Conclusions: Healthcare professionals viewed immersive VR as potentially useful but not yet ready for routine clinical implementation. Adoption in post-acute care should be guided by therapeutic purpose, accessibility, and integration into existing workflows rather than technological novelty alone. Future research and development should prioritise co-designed therapeutic content, patient selection, accessibility, workflow integration, and implementation support. Full article

Gap junctions (GJs) are channels that enable exchange of ions and small molecules between cells, and have been implicated in the development and maintenance of neuropathic pain. Injury-induced glial activation in sensory ganglia is associated with increased coupling by GJs, which in turn enhances neuronal excitability, contributing to pain signaling. Tonabersat (TON) was suggested to act as a GJ blocker with analgesic actions, but these claims have been disputed. Here we examined whether TON blocks GJs and whether it influences pain behavior in a mouse pain model. Gap junctional coupling was assayed by the dye coupling method in mouse liver and trigeminal ganglia. Pain behavior was tested in a mouse model of chemotherapy-induced pain, using von Frey filaments (tactile sensitivity), the acetone method (cold sensitivity) and hot plate (heat sensitivity). Intracellular dye injection showed that TON and the GJ blocker carbenoxolone (both 50 µM) inhibited gap junctional coupling by 70% and 82%, respectively. In the trigeminal ganglia, TON and carbenoxolone inhibited gap junctional coupling by 74 and 77%, respectively. TON selectively reduced heat and cold hypersensitivity, but not mechanical threshold. Carbenoxolone reduced all hypersensitivity types. No sex differences were observed. We conclude that both TON and carbenoxolone reduced coupling, indicating their potential to influence GJ-mediated coupling. In behavioral tests TON showed a selective effect for thermal hypersensitivity, but the underlying mechanism is unclear. Carbenoxolone produced a somewhat greater reduction in coupling compared with TON. These findings suggest that GJs play a role in pain pathways and highlight the need to explore whether other pain-relieving drugs act by blocking GJs. Full article

Sound source localization based on microphone arrays has attracted extensive research interest in the fields of speech communication, detection and tracking. However, conventional near-field beamforming typically assumes free-field propagation and ignores coherent ground reflections, which bias phase estimates at floor-mounted arrays and degrade localization accuracy. To address this, the total Green’s function is reformulated by embedding the image-source reflected path directly into the beamforming propagation model. Unlike conventional approaches that assume free-field propagation, this formulation enables phase compensation to jointly account for the direct and ground-reflected wavefronts. The in-phase superposition of signals is then realized through frequency-domain phase compensation, and the sound source position is estimated via the maximum likelihood criterion. Subsequently, a dual-mode operation mechanism of automatic broadband scanning and manual single-frequency analysis is implemented, with frequency-weighted wideband spatial spectrum processing for noise and aliasing suppression. Finally, a real-time sound source localization system based on a 4 × 4 MEMS array is designed. Experimental results show that sound source localization in a broad frequency band can be achieved at standoff distances of 0.1 m–0.3 m from the array plane, with a localization accuracy of less than 0.015 m. The proposed method demonstrates strong robustness against ground-reflection interference and has potential applications in acoustic monitoring, industrial fault diagnosis and other related areas. Full article

Objective feedback is important for improving welding training and reducing dependence on experienced instructors. This study proposes an image-based sensing framework for extracting motion and geometric features from videos acquired using a simple visualization system mounted inside a welding helmet during semi-automatic gas metal arc welding (GMAW) and manual gas tungsten arc welding (GTAW). The welding videos were acquired in real time, whereas the subsequent image-processing and quantitative feature-extraction procedures were performed offline. This visualization system consists of an instructor-side unit and a welder-side unit equipped with a prototype compact camera. Welding images were trimmed to 288 × 288 pixels and classified into eight regions for GMAW and six regions for GTAW using a U-Net-based semantic segmentation model. The segmented regions in GMAW included the arc, molten pool, groove, torch, wire, overlap regions, and background, whereas those in GTAW included the arc, bead, groove, electrode, filler wire, and background. Groove edges were detected using Canny edge detection and the Hough transform. The wire-tip position in GMAW and the electrode-tip position in GTAW were estimated using the arc centroid as an image-based positional proxy and normalized by the detected groove width to obtain normalized wire-tip and electrode-tip motion, respectively. In addition, the molten-pool width in GMAW and the bead width in GTAW were extracted and normalized using the same procedure to obtain groove-normalized geometric features. For the GMAW dataset, the segmentation model achieved a validation accuracy of 95.2% and a validation mean intersection over union (mIoU) of approximately 67.1%. For the GTAW dataset, the corresponding validation accuracy and validation mIoU were 96.6% and approximately 85.9%, respectively. The results showed that the proposed framework can successfully extract normalized wire-tip motion and molten-pool width in GMAW, as well as normalized electrode-tip motion and bead width in GTAW, from welding videos acquired from different welders. These findings demonstrate the potential of the proposed framework to extract quantitative motion and geometric features from welding videos, providing useful data for future welding training support and welding behavior analysis. Full article

In open-field agriculture, timely human activity recognition (HAR) is critical for anticipating worker actions and enabling proactive human–robot collaboration. This study developed an offline early HAR framework based on pre-segmented activity sequences. Long Short-Term Memory (LSTM) networks were used in conjunction with wearable inertial sensors mounted on the chest, cervical region, lumbar region, and right and left wrists. Accelerometer, gyroscope, and magnetometer signals were collected from 20 participants during an outdoor agricultural material-handling task, with a mobile ground robot serving as the receiving platform for the crate. Each activity was represented by cumulative prefixes from 30% to 100% of its duration. At the 30% observation ratio, the model achieved a macro-F1 score of 0.9314, compared with 0.9481 for the full sequence, corresponding to an absolute difference of 0.0167. Shapley Additive Explanations (SHAP) were also used to identify the body locations, sensor modalities, and signal channels that contributed most. The early decisions were mainly supported by sensors placed on the trunk, with wrist sensors providing complementary information, particularly for standing classification. Multimodal inertial information was also important. The most influential inputs were mainly gyroscope and magnetometer channels from the chest, cervical region, and lumbar region. In conclusion, the high performance at early observation ratios highlights the potential to support more adaptive and better-coordinated robot-assistance strategies. Full article

Background/Objectives: Precise genetic access to the zebrafish habenula remains limited by a scarcity of compact, sequence-defined cis-regulatory elements (CREs). Here, we integrated developmental expression mapping, deep-learning predictions on long-range sequences, and in vivo reporter assays to identify compact regulatory sequences driving habenular expression. Methods: Using a transgenic zebrafish line enriched for habenular reporter expression, we isolated GFP-positive cells from larval brains and profiled their transcriptomes via microarray. A subset of candidate genes enriched in this dataset was validated using whole-mount in situ hybridization across two developmental stages. This analysis identified genes with highly reproducible habenular expression, leading to the selection of the gng8 and ano2 loci for subsequent CRE characterization. We developed ZEN-former (Zebrafish EN-former), an Enformer-based sequence-to-function model trained on neuronal subclass chromatin accessibility profiles from the adult mouse brain. Results: The model demonstrated strong correlation between predicted and experimentally measured signals across held-out genomic regions. To prioritize regulatory candidates, we integrated ZEN-former predictions with available zebrafish ATAC-seq data, RepeatMasker annotations, and gene models, identifying two ~600 bp intervals at each gene locus. These selected intervals were combined to generate ~1.2 kb reporter constructs for gng8 and ano2 loci, which were then evaluated using Tol2 transposon mediated transgenesis assays in zebrafish. In transiently injected larvae, both constructs successfully drove reporter expression in the habenular region. Furthermore, the resulting stable transgenic lines displayed highly specific and reproducible habenular expression. Quantitative confocal analysis showed mean habenular labeling completeness values of 84.5% and 96.2% for the gng8- and ano2-derived lines, respectively. Conclusions: Together, these findings provide a proof of concept that sequence features learned from mammalian chromatin accessibility datasets can effectively guide the prioritization of functional regulatory elements across species in zebrafish. The compact regulatory constructs and stable transgenic lines generated here offer robust genetic tools for investigating habenular circuitry. Full article

Prostate cancer is the prototypical immunologically cold solid tumor, with objective response rates of only 3–5% to immune checkpoint inhibitors in unselected metastatic castration-resistant disease and an estimated 89.8% of tumors classified as immunologically ignorant. Three convergent features sustain this phenotype: low tumor mutational burden with defective Major Histocompatibility Complex class I antigen presentation; an immunosuppressive microenvironment dominated by regulatory T-cells, myeloid-derived suppressor cells, and M2 macrophages; and dense stromal and vascular barriers that exclude effector lymphocytes. Across these mechanisms, one compartment has received disproportionately little attention: the lymphatic system. Tumor-associated lymphatic remodeling driven by vascular endothelial growth factor C and D produces structurally abnormal vessels that impair antigen and dendritic cell trafficking to tumor-draining lymph nodes; the lymph nodes themselves are reprogrammed to a tolerogenic state by lymphatic endothelial cells expressing programmed death-ligand 1 and lacking costimulation and by regulatory T-cells that suppress effector egress. This review synthesizes evidence that in prostate cancer, immune coldness reflects not merely a problem of checkpoint engagement with the tumor but a failure of antigen trafficking at the lymphatic interface. We discuss therapeutic strategies that target this axis, such as lymphangiogenesis-inducing vaccines, lymph-node-directed checkpoint delivery, induction of intratumoral tertiary lymphoid structures and stromal reprogramming, as complements to existing immunotherapy. Targeting trafficking, not only checkpoints, may be the prerequisite for converting PCa from cold to hot. Full article

The events industry is facing mounting pressure to embed sustainability into core operations; yet, the mechanisms through which organizational initiatives translate into green practices remain underexplored. Drawing on Social Identity Theory, Stakeholder Theory, and Institutional Theory, this study examines the mediating role of Employee Environmental Identity (EEI) and the moderating role of Community Stakeholder Pressure (CSP) in the relationship between Sustainability Initiatives in Events (SIEs) and Green Operations (GOs). Data were collected from 448 employees in Saudi Arabian event management organizations and analyzed using PLS-SEM. The results reveal that SIE significantly enhances both EEI and GO. EEI partially mediates the SIE–GO relationship, while CSP strengthens all three hypothesized pathways, amplifying the effectiveness of sustainability initiatives and the translation of employee identity into operational outcomes. These findings advance theoretical integration across micro and macro perspectives and offer practical insights for managers, HR professionals, policymakers, and educators seeking to foster sustainability in event operations. By demonstrating the synergistic interplay among organizational initiatives, employee identity, and community pressure, this study underscores the importance of cultivating environmental self-concepts within a supportive stakeholder environment to achieve meaningful green outcomes aligned with Saudi Vision 2030. Full article

Deep-sea hydrothermal vents and cold seeps sustain highly productive animal communities through chemosynthetic symbioses, among which bathymodioline mussels are prominent examples. Bathymodioline gill bacteriocytes accommodate intracellular chemosynthetic symbionts, including sulfur- and/or methane-oxidizing bacteria depending on the host species, while remaining sheltered in an epithelium continuously exposed to environmental microorganisms, creating a fundamental immunological problem: how can an innate defense system remain effective without eliminating the microbial partners on which host nutrition depends? This review examines this problem through Bathymodiolus azoricus, integrating two decades of work on its cellular immunity, gill transcriptome, microbial challenge responses and symbiosis biology with recent mechanistic studies from related bathymodiolines. Central to the present synthesis are previously reported B. azoricus observations showing that gill tissue can mount local transcriptional responses to bacterial challenge, while hemolymph serum differentially modulates immune-gene expression following exposure to symbiont preparations or non-symbiotic Vibrio. Immune-gene expression also varies along the anterior–posterior gill axis, with lower expression in the posterior budding zone than in mature anterior filaments. We interpret this zonation primarily as a feature of tissue maturation rather than demonstrated active immune suppression, consistent with evidence that newly formed filaments are initially aposymbiotic and become colonized only after formation. Together, these observations evoke a host–symbiont–pathogen triad in which local gill-tissue responses, systemic humoral modulation and gill development constitute interacting levels of immune organization and compartmentalization. As a working hypothesis, we propose that this triad is reconciled principally through spatial and developmental compartmentalization of immune competence rather than through generalized immune suppression, predicting that immune-gene expression should track gill maturation state rather than symbiont occupancy per se. We consider this tissue-level model alongside comparative evidence for putative symbiont-uptake mechanisms, post-engulfment microbial discrimination, lysosomal regulation, symbiont digestion and bacteriocyte turnover, including the mTORC1-dependent phagosome-digestion checkpoint demonstrated in Bathymodiolus japonicus. Rather than assuming that these mechanisms are conserved across species, we distinguish explicitly between findings established in B. azoricus, evidence from other bathymodiolines and canonical pathways used as mechanistic context. We conclude by identifying unresolved components of B. azoricus immunity, including the prophenoloxidase system, the broader antimicrobial-peptide repertoire and the relationship between cellular checkpoints and tissue-level gill zonation, and consider the prospective biotechnological relevance of mechanisms that tolerate persistent microbial symbiosis without loss of immune vigilance. Full article

Accurate measurement of vibro-acoustic transfer functions is essential for ship noise control. Because direct testing requires high-power excitation sources that are difficult and costly to deploy, the reciprocity method has attracted increasing attention. Its application to full-scale ships, however, has long been hindered by an unresolved theoretical question: whether hull-mounted acoustic coatings compromise force–sound reciprocity. To answer this question, this study combines theoretical analysis, numerical simulation, and anechoic water-tank experiments to investigate a typical horn-type cavity acoustic coating. Theoretical analysis shows that, because its complex stiffness tensor remains symmetric, a linear viscoelastic coating with geometrically asymmetric cavities still preserves reciprocity. Numerical simulations of a stiffened double-layer cylindrical shell covered with the coating show that the forward and reciprocal transfer functions coincide to well within 1 dB over the entire computed band. Anechoic water-tank experiments on a scaled model show that applying the coating raises the band-averaged reciprocity error by only 0.2 dB, from 1.4–1.5 dB to 1.6–1.7 dB in the 2–5 kHz band. These results provide evidence that, for the tested coating and structural configuration under anechoic conditions, the horn-cavity coating introduces no significant principle-based error into reciprocity testing—a first quantitative step towards removing the long-standing theoretical obstacle to applying reciprocity methods to coated, full-scale ships. Full article

Green steel transitions in emerging economies are currently planned around large integrated plants, while the small and medium enterprise (SME) segment that dominates finished steel output remains poorly characterized. This review consolidates the environmental evidence on India’s secondary steel sector, which supplies nearly 65% of national finished steel through more than 8500 units spanning coal-based direct reduced iron (DRI), induction furnace, electric arc furnace, steel re-rolling, foundry, and forging operations. Using an integrative scoping design that combines the peer-reviewed literature, government publications, industrial energy audits, and cluster assessments, the review maps process routes, regional clusters, product flows, and energy and carbon footprints, identifying the source, reference year, system boundary, and confidence level of each principal value. The sector consumed approximately 11.8 Mtoe (137,234 GWh) and emitted an estimated 58.2 Mt CO₂ in 2019–2020, with coal-based DRI contributing about 52% of sector emissions, 60% of steelmaking-route emissions, and roughly twice the specific energy consumption of international benchmarks. Water use remains a critical evidence gap. The resulting route- and cluster-resolved baseline provides the foundation from which green production pathways for SME steel systems can be identified and the plant-level measurement priorities that credible net-zero planning requires can be specified. Full article

Climate change perception among youth has gained increasing scholarly attention; however, immigrant youth remain underrepresented in empirical research despite navigating climate change impacts across multiple sociocultural and geopolitical contexts. This study investigates (1) immigrant youths’ beliefs about climate change, (2) how climate risks are perceived across space and time, and (3) how they construct their climate change beliefs and associated risks. Drawing on Social Constructivism, and Risk Perception Theory, the study employs a qualitative descriptive design using eight focus group discussions with 41 immigrant youth aged 14–18 in Calgary, Canada. Reflexive thematic analysis reveals that immigrant youth widely recognise climate change as real and intensifying, with beliefs shaped through lived and observed environmental experiences, social interaction, family narratives, and transnational comparisons rather than abstract scientific reasoning alone. Climate risk perception emerges as complex and relational. Participants associated climate change with impacts on health, wellbeing, food security, and everyday life; however, they often perceived its most severe consequences as temporally and spatially distant. This produces a notable “belief–risk gap,” where acceptance of climate change does not translate into a strong sense of personal vulnerability or urgency. Risk perceptions are mediated by everyday experiences, institutional trust in the host country, and comparisons with other global crises. The findings highlight the critical role of transnational experiences in shaping climate understanding and advance an integrated interpretation linking socially constructed climate knowledge with perceptions of risk and psychological distance, with implications for climate communication and public health communication strategies for immigrant youth. Full article

Among the various brain–computer interface (BCI) modifications used in post-stroke rehabilitation, BCI systems combined with functional electrical stimulation (FES) are considered the most effective. As a preliminary step toward optimizing such systems for clinical application, it remains unclear whether using electroencephalography (EEG) alone versus a hybrid EEG and functional near-infrared spectroscopy (fNIRS) approach affects real-time three-class BCI–FES control performance in healthy individuals. In a blind randomized study, 16 healthy volunteers completed five BCI–FES training sessions across three days. In one group, FES of wrist extensor muscles was driven by a hybrid EEG–fNIRS classifier; in the other, by EEG only. Classification accuracy, sense of agency, attention, and physical comfort were assessed. No statistically significant between-group differences were found in any outcome measure (p > 0.05). Median real-time three-class classification recall was 53.5% in the hybrid group and 57.3% in the EEG-only group. The median agency score reached approximately 75% of the maximum possible value in both groups. Simulation analysis showed comparable accuracy for unimodal fNIRS-only and EEG-only classifiers. Genetic algorithm-based channel selection identified C3 and C4 as the most informative EEG channels, while optimal fNIRS placement required individual optimization. Within the constraints of the classification and fusion pipeline used here, these findings suggest that signal acquisition modality does not significantly influence BCI–FES performance or sense of agency in healthy subjects. The complete EEG–fNIRS dataset is publicly available through NITRC. Full article

Reliable finite-horizon forecasting of chaotic dynamics is challenging because small approximation errors grow rapidly during recursive prediction. This study presents a controlled comparison of data-driven and physics-regularized forecasting methods for the Lorenz and Rössler systems. The proposed Hybrid Physics-Informed Feedforward Neural Network (Hybrid PI-FNN) learns a discrete state-transition map from a ten-state observation window through a five-step recursive rollout. Unlike conventional continuous-coordinate physics-informed neural networks, physical consistency is imposed using fourth-order Runge–Kutta transition targets derived from the known governing equations. The physics weight is selected using chronological recursive validation and evaluated against an architecturally identical multi-step FNN with $\lambda =0$. Conventional FNN, LSTM, Echo State Network (ESN), Autoregressive AR(10), and Dynamic Mode Decomposition baselines are also evaluated using untouched test trajectories. For the 1000-step Lorenz test rollout, the ESN achieved the lowest mean squared error (MSE) of 0.1701, followed by the LSTM with 22.9962. The Hybrid PI-FNN produced an MSE of 95.8157, compared with 87.9260 for its $\lambda =0$ ablation; therefore, physics regularization did not improve Lorenz test MSE, although their forecast horizons at a 10% normalized-error threshold were similar (273 and 272 steps, respectively). For the Rössler system, the Hybrid PI-FNN reduced recursive MSE from 0.2202 for the $\lambda =0$ ablation to 0.0834, corresponding to a 62.11% reduction, while both models completed the maximum evaluated 1000-step forecast horizon. Nevertheless, the ESN again achieved the lowest Rössler MSE of approximately $8.04\times {10}^{-5}$. Finite-horizon correlation-dimension analysis, exact governing-equation Lyapunov spectra, computational-cost comparisons, and five-seed paired experiments were additionally conducted. The exact spectra confirmed one positive, one approximately neutral, and one negative exponent for each system, indicating chaotic but not hyperchaotic behavior. The paired multi-seed analysis did not establish a statistically significant forecasting advantage from physics regularization. These findings show that higher-order physics consistency can benefit particular systems and configurations, but it does not guarantee universal superiority in recursive chaotic forecasting. Full article